Benjamini Hochberg

This program applies the Benjamini Hochberg correction to a column of P values. The significant P values are extracted and the adjusted Benjamini-Hochberg P values are computed as well. The FDR is 0.01 and the threshold is 0.05 by default.

Manual :

1- install Julia v1.6 or higher free programming language and install packages :

ArgParse : add ArgParse

CSV : add CSV

DataFrames : add DataFrames

StatsBase : add StatsBase

MultipleTesting : add MultipleTesting

2- Install Perl and Gnu parallel for parallel file processing

3- unzip the software

4- copy your n tables in csv (TAB delimitated by default) files in the “data” directory.

The tables must have at least one columns labeled Pvalue.

5- execute the software by the command :

julia BenjHochberg-011.jl [-s SEP] -f FILE [-d FDR] [-t THR] [-h]

optional arguments:

-s, --sep SEP separator for CSV tables (default: '\t')

-f, --file FILE file with at least one columns labeled Pvalue.

-d, --fdr FDR FDR ex. 0.01 (type: Float64, default: 0.01)

-t, --thr THR Qvalue Threshold ex. 0.05 (type: Float64, default: 0.05)

-h, --help show this help message and exit

example :

julia BenjHochberg-005.jl -f data/test.csv

julia BenjHochberg-0xx.jl -d 0.001 -t 0.05 -f data/test.csv # FDR = 0.001 significance threshold = 0.05

The FDR is 0.01 and the threshold is 0.05 by default.

To process files in parallel, edit the conf.txt file and start processing with the command perl parallel_BH-0.2.pl

6- processed file is in the “result” directory.

7- significant results are in "significant" directory.

for more explanations of Pvalue with FDR control, see here